• Korean Journal of Optics and Photonics
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• v.18 no.4
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• pp.246-255
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• 2007

The floating image system (FIS) is a device to display input source in the space between fast surface of the display and an observer and it provides pseudo 3D depth to an observer when input source as real object or 2D image was displayed through the optical lens system in the FIS. The Advanced floating image system (AFIS) was designed to give more effective 3D depth than existing FIS by adding front and rear depth cues to the displayed stereogram, which it was used as input source. The magnitude of disparity and size of stereogram were strongly related each other and they have been optimized for presenting 3D depths in a non-optical lens systems. Thus, if they were used in optical lens system, they will have reduced or magnified parameters, leading to problem such as providing incorrect 3D depth cues to an observer. Although the size of stereogram and disparity were demagnified by total magnifying power of optical system, the viewing distance (VD) from the display to an observer and base distance (BD) for the gap between the eyes were fixed. For this reason, the quantity of disparity in displayed stereogram through the existing FIS has not kept the magnifying power to the total optical system. Therefore, we proposed the methods to provide correct 3D depth to an observer by compensating quantity of disparity in stereogram which was satisfied to keep total magnifying power of optical lenses system by AFIS. Consequently, the AFIS provides a good floating depth (pseudo 3D) with correct front and rear 3D depth cues to an observer.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.37-42
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• 2018

With advancements in digital image production technology, the branch of stereoscopic image technology has also been undergoing active development. Accordingly, research and development on cutting-edge display products for mounting stereoscopic images are currently being pursued. There are various problems that can occur when viewing 3D images. Because viewers feel visual fatigue while perceiving the depth of the images provided via an artificial method, a negative human factor such as visual fatigue has become one of the most prominent concerns, especially as it is a factor that affects the ongoing maintenance of 3D images. Therefore, by identifying the factors affecting the depth of the graphic images provided in 2D images, and subsequently using this information to develop an image processing method, we conducted depth-related experiments and analysed them under the assumption that stereoscopic images could be reproduced without visual fatigue. Thus, we analysed the most significant factors related to depth and verified the interactions by performing depth-related factors-based ANOVA variance analysis by differentially applying the texture, colour temperature, and contrast ratio to graphic images. We determined the significance of the factors related to depth and proposed a method to improve depth based on an analysis of the results of the experiments conducted in this study.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.309-316
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• 2014

In this paper, we propose an efficient detph map creation method using Graph Cut and Discrete Wavelet Transform. First, we have segmented the original image by using Graph Cut to process with its each areas. After that, the information which describes segmented areas of original image have been created by proposed labeling method for segmented areas. And then, we have created four subbands which contain the original image's frequency information. Finally, the depth map have been created by frequency map which made with HH, HL subbands and depth information calculation along the each segmented areas. The proposed method can perform efficient depth map creation process because of dynamic allocation using depth information. We also have tested the proposed method using PSNR(Peak Signal to Noise Ratio) method to evaluate ours.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6A
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• pp.458-463
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• 2012

In this paper, we propose a direct depth map acquisition method for the convergence camera array as well as the parallel camera array. The conventional methods perform image rectification to reduce complexity and improve accuarcy. However, image rectification may lead to unwanted consequences for the convergence camera array. Thus, the proposed method excludes image rectification and directly extracts depth values using the epipolar constraint. In order to acquire a more accurate depth map, occlusion detection and handling processes are added. Reasonable depth values are assigned to the obtained occlusion region by the distance and color differences from neighboring pixels. Experimental results show that the proposed method has fewer limitations than the conventional methods and generates more accurate depth maps stably.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1311-1316
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• 2021

In this paper, we present a bifocal stereo camera system combining two cameras with different focal length cameras to generate stereoscopic image and their corresponding depth map. In order to obtain the depth data using the bifocal stereo camera system, we perform camera calibration to extract internal and external camera parameters for each camera. We calculate a common image plane and perform a image rectification for generating the depth map using camera parameters of bifocal stereo camera. Finally we use a SGM(Semi-global matching) algorithm to generate the depth map in this paper. The proposed bifocal stereo camera system can performs not only their own functions but also generates distance information about vehicles, pedestrians, and obstacles in the current driving environment. This made it possible to design safer autonomous vehicles.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.8-17
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• 2011

Recently, fusion camera systems that consist of depth sensors and color cameras have been widely developed with the advent of a new type of sensor, time-of-flight (TOF) depth sensor. The physical limitation of depth sensors usually generates low resolution images compared to corresponding color images. Therefore, the pre-processing module, such as camera calibration, three dimensional warping, and hole filling, is necessary to generate the high resolution depth map that is placed in the image plane of the color image. However, the result of the pre-processing step is usually inaccurate due to errors from the camera calibration and the depth measurement. Therefore, in this paper, we present a depth map upsampling method robust these errors. First, the confidence of the measured depth value is estimated by the interrelation between the color image and the pre-upsampled depth map. Then, the detailed depth map can be generated by the modified kernel regression method which exclude depth values having low confidence. Our proposed algorithm guarantees the high quality result in the presence of the camera calibration errors. Experimental comparison with other data fusion techniques shows the superiority of our proposed method.

• Science of Emotion and Sensibility
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• v.19 no.3
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• pp.81-88
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• 2016

The purpose of this research was to analyze several factors that can affect the respiration rate measurement using the Creative Senz3D depth camera. Depth error and noise of the depth camera were considered as affecting factors. Ambient light was also considered. The result of this study showed that the depth error was increased with an increase of the distance between subject and depth camera. The result also showed depth asymmetry in the depth image. The depth values measured in right region of the depth image was higher than real distance and depth values measured in left of the depth image was lower than real distance. The difference error of the depth was influenced by the orientation of the depth camera. The noise created by the depth camera was increased as the distance between subject and depth camera was increased and it decreased as the window size was increased which was used to calculate noise level. Ambient light seems to have no influence on the depth value. In real environment, we measured respiration rate. Participants were asked to breathe 20 times. We could find that the respiration rate which was measured from depth camera shows excellent agreement with that of participants.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.815-816
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• 2008

In this paper, we evaluate depth image preprocessing for 3D data service based on DIBR over T-DMB. We evaluate two preprocessing methods of depth images. These are gaussian smoothing and adaptive smoothing. The results show that adaptive smoothing is more suitable for images with sharp transition of depth.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.67-70
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• 2009

This paper proposes an algorithm for creating stereoscopic video from a monoscopic video. A viewer uses depth perception clues called a vanishing point which is the farthest from a viewer's viewpoint in order to perceive depth information from objects and surroundings thereof to the viewer. The viewer estimates the vanishing point with geometrical features in monoscopic images, and can perceive the depth information with the relationship between the position of the vanishing point and the viewer's viewpoint. In this paper, we propose a method to estimate a vanishing point with edge direction histogram in a general monoscopic image and to create a depth map depending on the position of the vanishing point. With the conversion method proposed through the experiment results, it is seen that stable stereoscopic conversion of a given monoscopic video is achieved.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1666-1669
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• 2002

In the process of creating architectural scenes from photographs using Model-based Stereo 〔1〕, the geometric model is used as prior information to solve correspondence problems and recover the depth or disparity of real scenes. This paper presents an Image Subregioning algorithm that divides left and right images into several rectangular sub-images. The division is done according to the estimated depth of real scenes using a Heuristic Approach. The depth difference between the reality and the model can be partitioned into each depth level. This reduces disparity search range in the Similarity Function. For architectural scenes with complex depth, experiments using the above approach show that accurate disparity maps and better results when rendering scenes can be achieved by the proposed algorithm.